Learning Machine Learning

Introductory MOOCs

 

Neural Networks (and Deep Learning)

 

Links to check

http://stats.stackexchange.com/questions/71184/cross-validation-or-bootstrapping-to-evaluate-classification-performance

http://www.datasciencecentral.com/profiles/blogs/deploying-predictive-models

http://www.datasciencecentral.com/profiles/blogs/why-so-many-machine-learning-implementations-fail

http://www.analyticbridge.com/profiles/blogs/regression-logistic-regression-and-maximum-entropy

http://www.analyticbridge.com/group/analyticaltechniques/forum/topics/logit-vs-probit-regression

http://www.analyticbridge.com/forum/topics/how-to-determine-if-a-sample-is-representative

http://www.datasciencecentral.com/profiles/blogs/naive-bayes-for-dummies-a-simple-explanation

http://www.datasciencecentral.com/profiles/blogs/how-to-lie-with-visualizations-statistics-causation-vs

http://www.datasciencecentral.com/profiles/blogs/correlation-does-not-imply-causation

http://www.datasciencecentral.com/profiles/blogs/simple-guide-for-selecting-statistical-tests-when-comparing

http://www.datasciencecentral.com/profiles/blogs/tutorial-how-to-detect-spurious-correlations-and-how-to-find-the-

http://www.datasciencecentral.com/profiles/blogs/12-algorithms-every-data-scientist-should-know

http://www.datasciencecentral.com/profiles/blogs/12-most-popular-data-science-blogs

http://www.datasciencecentral.com/profiles/blogs/40-techniques-used-by-data-scientists

http://www.datasciencecentral.com/profiles/blogs/17-short-tutorials-all-data-scientists-should-read-and-practice

https://www.quora.com/What-makes-a-model-interpretable/answer/Claudia-Perlich?srid=cgo

 

 

  3 comments for “Learning Machine Learning

  1. Katie
    03/03/2018 at 09:35

    I feel as though I have wasted a lot of time forgetting the mathematics I was so good at once before, I love the article!!

    I feel so very far behind i can’t wait to read more

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